Welcome to the exciting world of 3D Gaussian Splatting! In this guide, we will walk you through the process of reproducing the Gaussian-Splatting software developed by Inria and the Max Planck Institut for Informatik, now utilizing C++ and CUDA. This comprehensive guide will help you get started and troubleshoot any hiccups along the way!

Getting Started

Before diving into the implementation, it’s crucial to ensure you have the right prerequisites in place. Let’s break it down into software and hardware requirements.

Software Prerequisites

• Linux (tested with Ubuntu 22.04); Windows may not be compatible.
• CMake version 3.24 or higher.
• CUDA version 11.7 or higher.
• Python with development headers.
• libtorch: Follow instructions in the libtorch section of this README.
• Other dependencies will be handled by the CMake script.

Hardware Prerequisites

• NVIDIA GPU with CUDA support (successfully tested with RTX 4090, RTX A5000, 3090Ti, A100).
• Minimum compute capability tested was 8.0.

Building the Project

Once you have the prerequisites ready, it’s time to build the project!

Build Instructions

bash
git clone --recursive https://github.com/MrNeRF/gaussian-splatting-cuda
cd gaussian-splatting-cuda
wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip
unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external
rm libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip
cmake -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build -- -j

Command-Line Options

Once built, you can utilize various command-line options for execution. Here’s a sample:

bash
./build/gaussian_splatting_cuda -d path_to_data -o path_to_output -i 1000

Understanding the Code Through Analogy

If you’ve ever tried to prepare a new recipe from scratch, the steps involved can be likened to coding in C++ and CUDA to implement Gaussian Splatting. Here’s how:

• Gathering Ingredients (Prerequisites): Just like a cook needs to gather all ingredients before starting, you must ensure all software and hardware prerequisites are in place before you begin coding.
• Following the Recipe (Building the Project): A recipe provides step-by-step guidance, similar to the build instructions you follow to compile and create your program.
• Taste Testing (Command-Line Options): Before serving your dish, you often taste and adjust the flavors. Similarly, you can run the implemented code with various options and adjust parameters to get the desired results.

Troubleshooting

Should you run into issues while following this guide, here are some troubleshooting ideas:

• Build Failures: Ensure all dependencies are correctly installed. Often, missing libraries cause build failures.
• Execution Errors: Double-check command-line arguments. Ensure the paths are correct and point to the appropriate directories.
• Performance Issues: Use profiling tools to identify bottlenecks in the code. Remember, optimization is a continuous process!

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Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

We hope this guide has provided you with a clear pathway to reproduce the 3D Gaussian Splatting software and that you’re now ready to embark on your own journey of rendering greatness! Happy coding!